ISTIFADA : Jurnal Ekonomi dan Lembaga Keuangan Syariah
Vol. 2 No. 02 (2026): ISTIFADA : Jurnal Ekonomi Dan Lembaga Keuangan Syariah

Analysis Netizen Sentiment towards Corporate Social Responsibility (CSR) of Bank Syariah Indonesia (BSI) on Social Media Using Machine Learning Algorithms

Nur Laily Hidayati (STIES Babussalam Jombang)
Jafar Shiddiq (STIES Babussalam Jombang)
Muhammad Khoirun Nasirin (STIES Babussalam Jombang)



Article Info

Publish Date
14 Aug 2026

Abstract

The development of social media has change method public assess and respond implementation of Corporate Social Responsibility (CSR) by institutions financial sector , including Bank Syariah Indonesia (BSI). Opinions expressed by netizens through various social media platforms reflect level acceptance , satisfaction , and expectation public on the CSR programs being implemented . Research This aim For analyze netizen sentiment towards Implementation of CSR of Bank Syariah Indonesia (BSI) on social media use algorithm machine learning , at the same time identify most topics​ get attention public . Research use approach quantitative with method analysis sentiment based text mining . Data obtained through the web scraping process from social media platforms that contain keywords related to BSI CSR during period observation certain . Stages study covering data collection , pre-processing text (case folding, tokenization, stopword removal, stemming), labeling sentiment , extraction feature use Term Frequency-Inverse Document Frequency (TF-IDF), as well as classification use algorithm Support Vector Machine (SVM), Naïve Bayes , and Random Forest . Model performance was evaluated use metric accuracy , precision , recall , and F1-score . Research results show that majority netizen sentiment towards BSI's CSR program is positive by 68.4%, followed by sentiment neutral by 18.7%, and sentiment negative by 12.9%. The SVM algorithm provides performance best with level accuracy of 92.4%, surpassing Naïve Bayes (88.6%) and Random Forest (90.8%) . Keyword analysis show that issue education , empowerment of MSMEs, assistance social , conservation environment and sustainability become the most topics appreciated public . On the contrary , sentiment negative more Lots triggered by perception about lack of program equity , transparency reporting , and effectiveness implementation in several regions. Findings study show that analysis sentiment based machine learning capable become instrument effective evaluation​ in measure perception public in real-time, so that can support taking decision BSI 's strategic increase quality , transparency , and sustainability of aligned CSR programs with principle maqashid sharia and sustainable finance

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Journal Info

Abbrev

istifada

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Subject

Description

ISTIFADA: Jurnal Ekonomi dan Lembaga Keuangan Syariah adalah jurnal ilmiah yang diterbitkan oleh Prodi Perbankan Syariah STIES Babussalam. Jurnal ini berfokus pada publikasi karya ilmiah di bidang ekonomi Islam, perbankan syariah, dan lembaga keuangan syariah, baik dalam konteks teori maupun ...